Abstract
Face image retrieval is to find from a dataset all images containing the same person in the query image. Automatic face retrieval has seen fast development in recent years, although humans still appear to be the better performer on this task. This paper reports a study towards understanding human performance on retrieving unfamiliar faces. Wild Web face images are utilized in the study, and two experiments are designed to assess human performance and behavior on the retrieval task. The experiments help to identify a set of important features and also to understand how human behaved when facing the task of retrieving unfamiliar faces. Such observations/conclusions may provide guidelines for improving existing automated algorithms.
| Original language | English (US) |
|---|---|
| Title of host publication | MM 2015 - Proceedings of the 2015 ACM Multimedia Conference |
| Publisher | Association for Computing Machinery, Inc |
| Pages | 1287-1290 |
| Number of pages | 4 |
| ISBN (Print) | 9781450334594 |
| DOIs | |
| State | Published - Oct 13 2015 |
| Event | 23rd ACM International Conference on Multimedia, MM 2015 - Brisbane, Australia Duration: Oct 26 2015 → Oct 30 2015 |
Other
| Other | 23rd ACM International Conference on Multimedia, MM 2015 |
|---|---|
| Country/Territory | Australia |
| City | Brisbane |
| Period | 10/26/15 → 10/30/15 |
Keywords
- Face image retrieval
- Human performance
ASJC Scopus subject areas
- Media Technology
- Computer Graphics and Computer-Aided Design
- Computer Vision and Pattern Recognition
- Software